Magnetic resonance imaging (“MRI”) is a noninvasive imaging method widely used for medical diagnostics. To date, MRI methods for tracking the motion of an object over relatively long periods of time have been based on spatially modulating magnitude of the specimen magnetization according to a specific grid pattern, and observing the deformation of this grid pattern as motion occurs. In order to quantify the displacement vector of any small volume element (voxel), the positions of the grid lines and their intersection points are precisely defined. This usually requires human assistance, and precision is limited by image resolution or voxel size. The motion of voxels between grid lines cannot be measured directly, and interpolation methods are used to estimate motion.
Other MRI methods measure voxel velocity by subjecting the transverse magnetization to a biphasic gradient pulse before readout, so that stationary spins do not accumulate a net phase change, while spins with nonzero velocity components along the gradient direction accumulate a phase change. By measuring such phase changes, one or more velocity components can be derived. While phase-contrast velocity mapping generally provides high spatial resolution and simple data processing, it is generally unsuitable for motion tracking, as it requires integration of velocity vectors from multiple measurements and mathematically tracking voxel positions. These integrations and voxel position tracking are difficult and prone to error.